If you’re interested in big ecological datasets, natural history, and predictive cross-scale ecology (like we are) then you should check out the upcoming Gordon Research Conference (GRC) on Unifying Ecology Across Scales (July 28 – Aug 2) and the associated Gordon Research Seminar (GRS;

Many researchers are becoming more aware of the importance of reproducibility.Although reproducibility involves a diverse array of topics and tools, one rOpenSci package has gained considerable attention for enabling reproducible analysis pipelines in R: targets, by Will Landau. Why a targets workshop?

Research data and software rely heavily on the technical and social infrastructure to disseminate, cultivate, and coordinate projects, priorities, and activities. The groups that have stepped forward to support these activities are often segmented by aspects of their identity - facets like discipline, for-profit versus academic orientation, and others.

In November of 2022, the Research Software Alliance (ReSA) and the Netherlands eScience Center organized a two-day international workshop titled “The Future of Research Software.” In the workshop, funding organizations joined forces to explore how they could effectively contribute to making research software sustainable. The workshop had many participants from all continents and was a huge success.

Researchers, librarians, policy makers, and practitioners often complain about the scholarly publishing system, but the system also offers exciting opportunities to contribute to innovations in the way academic findings are disseminated and evaluated.

Three members of the rOpenSci team - Scott Chamberlain, Jenny Bryan, and Rich FitzJohn - as well as many community members will give talks at useR!2019. Many other package authors, maintainers, reviewers and unconf participants will be there too. Don’t hesitate to ask them about rOpenSci packages, software peer review, community, or just say hello if you’re looking for a friendly face. We’ve listed their talks for you.

You can find members of the rOpenSci team at various meetings and workshops around the world. Come say ‘hi’, learn about how our software packages can enable your research, or about our process for open peer software review and onboarding, how you can get connected with the community or tell us how we can help you do open and reproducible research.Where’s rOpenSci?

Motivation A few weeks ago, as part of the rOpenSci Unconference, a group of us (Sean Hughes, Malisa Smith, Angela Li, Ju Kim, and Ted Laderas) decided to work on making the UMAP algorithm accessible within R. UMAP (Uniform Manifold Approximation and Projection) is a dimensionality reduction technique that allows the user to reduce high dimensional data (multiple columns) into a smaller number of columns for visualization purposes (github,

tl;dr : we propose three calls to action:Share your curricular materials in the open.Participate in the rOpenSci Education profile series.Discuss with us how you want to be involved in rOpenSci Educators’ Collaborative.

In the first post of this series, we sketched out some of the common challenges faced by educators who teach with R across scientific domains. In this post, we delve into what makes a “good” educational resource for teaching science with R. For instructors teaching sciences with R, there are a number of open educational resources that they can reuse, tailor to their own teaching style, or use to inspire them in creating their own materials.